Computational solvent mapping methods place molecular probes - small molecules or functional groups - on a protein surface in order to identify the most favorable binding positions. X-ray crystallography and NMR show that organic solvents with different sizes and polarities cluster at a limited number of sites on a protein. A recently developed mapping algorithm reliably identifies the consensus sites at which different probe molecules bind. These sites are in good agreement with the available experimental data. A very important result is that the consensus sites in enzymes are major subsites of the substrate binding site, and the amino acid residues that interact with the probes also bind the specific ligands (substrates, inhibitors, and transition state analogs) of the enzyme. Thus, computational mapping can be used for the identification and characterization of functional sites. The approach is less sensitive to variations in the structure of the protein than docking methods, and is remarkably robust against changes in the algorithm and energy parameters. The goals of this proposal include the development of software for high-throughput automatic mapping, validation of the approach by the mapping of a number of well understood enzymes, and application of the method to as many poorly characterized enzymes as possible. The results are expected to provide a substantial body of new information on enzyme binding sites, and at the very least should suggest which residues should be studied by site-directed mutation experiments. Solvent mapping will also be tested for its ability to identify functional sites in other types of proteins. A reliable mapping method will be particularly useful, as structural genomics approaches are likely to produce structures for an increasing number of poorly characterized proteins, and there are very few computational methods for identifying functional sites on the basis of protein structure, As a second application, amino acids will be used as probes, and the relationship between favorable binding positions of individual amino acid residues and their actual positions in bound peptides will be studied.